I. Introduction
Comprehensive urban traffic information can benefit urban citizens' daily life and improve urban transportation efficiency. Accurate predictions of such traffic information are of great importance for route planning, navigation, and other mobility services. Urban traffic prediction generally applies traffic models to analyze various historical and real-time traffic data to predict traffic conditions in terms of the number of moving objects (e.g., vehicles) in the future. Thanks to the popularity of ubiquitous sensing and Intelligent Transportation Systems (ITS) in recent years, we can gather unprecedented mobility data by exploiting various mobile devices (e.g., smartphones and on-board GPS devices). Such emerging big data availability makes accurate traffic predictions viable.